Yanfei Kang
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- Stock Market Forecasting Methods 13
- Forecasting Techniques and Applications 13
- Signal Processing top 5%
- Time Series Analysis and Forecasting 12
- Environmental Engineering top 10%
- Wind and Air Flow Studies 2
- Artificial Intelligence top 10%
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- Complex Systems and Time Series Analysis 3
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- Energy Load and Power Forecasting 2
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- Supply Chain and Inventory Management 2
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- Atmospheric and Environmental Gas Dynamics 2
- Co-authors
- Rob J. HyndmanFeng LiZizhuo WangYixiong ChenKate Smith‐MilesXixi LiFotios PetropoulosDanijel Belušić
- Journals
- SHILAP Revista de lepidopterología (1 paper)European Journal of Operational Research (3 papers)Journal of Business Research (1 paper)
- Partner nations
- ChinaAustraliaUnited Kingdom
In The Last Decade
Yanfei Kang
26 papers receiving 793 citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Management Science and Operations Research 286
- Signal Processing 162
- Environmental Engineering 107
- Health Informatics 8
- Artificial Intelligence 179
Countries citing papers authored by Yanfei Kang
This map shows the geographic impact of Yanfei Kang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yanfei Kang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yanfei Kang more than expected).
Fields of papers citing papers by Yanfei Kang
This network shows the impact of papers produced by Yanfei Kang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yanfei Kang. The network helps show where Yanfei Kang may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yanfei Kang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 13 | |
| 4 | 2024 | 8 | |
| 5 | 2023 | 3 | |
| 6 | 2023 | 1 | |
| 7 | 2023 | 39 | |
| 8 | 2022 | 109 | |
| 9 | 2022 | 12 | |
| 10 | 2022 | 12 | |
| 11 | Improving forecasting with sub-seasonal time series patterns | 2021 | 1 |
| 12 | 2020 | 15 | |
| 13 | 2020 | 56 | |
| 14 | Probabilistic forecasting with temporal convolutional neural networkbreakdown → | 2020 | 255 |
| 15 | Time Series Feature Extraction [R package tsfeatures version 1.0.2] | 2020 | 5 |
| 16 | 2017 | 118 | |
| 17 | 2014 | 37 | |
| 18 | 2014 | 1 | |
| 19 | 2013 | 2 | |
| 20 | 2012 | 6 |
About Yanfei Kang
Yanfei Kang is a scholar working on Management Science and Operations Research, Signal Processing and Ecological Modeling, having authored 27 papers that have together received 818 indexed citations. Recurring topics across this work include Stock Market Forecasting Methods (13 papers), Forecasting Techniques and Applications (13 papers), Time Series Analysis and Forecasting (12 papers), Complex Systems and Time Series Analysis (3 papers), Wind and Air Flow Studies (2 papers), Energy Load and Power Forecasting (2 papers), Supply Chain and Inventory Management (2 papers) and Atmospheric and Environmental Gas Dynamics (2 papers). The work is most often cited by research in Management Science and Operations Research (286 citations), Signal Processing (162 citations) and Environmental Engineering (107 citations). Yanfei Kang has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Rob J. Hyndman, Feng Li, Zizhuo Wang, Yixiong Chen, Kate Smith‐Miles, Xixi Li, Fotios Petropoulos, Danijel Belušić, Spyros Makridakis and Evangelos Spiliotis. Their work appears in journals such as SHILAP Revista de lepidopterología, European Journal of Operational Research and Journal of Business Research.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.